Principles of Artificial IntelligenceA classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of the control strategies used. Principles of Artificial Intelligenceevolved from the author's courses and seminars at Stanford University and University of Massachusetts, Amherst, and is suitable for text use in a senior or graduate AI course, or for individual study. |
From inside the book
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... costs to arcs, to represent the cost of applying the corresponding rule. We use the notation c (ni, n,) to denote the cost of an arc directed from node n, to node n,. It will be important in some of our later arguments to assume that these ...
... costs of the associated arcs). We call this process of applying the successor operator to a node, expanding the node. The successor operator depends in an obvious way on the rules. Expanding s, the successors of s, ad infinitum, makes ...
... cost of a path from s to n in the search tree can be computed by summing the arc costs encountered in the tree while tracing back from n to s. In problems for which no arc costs are given, we assume that the arcs have unit cost.) When a ...
... costs of the paths to the descendants of node 2 in the search graph (namely, the paths to nodes 4 and 5) are recomputed. These costs are now also lower than before, with the result that the parent of node 4 is changed from node 6 to ...
... cost of the path and the cost of the search required to obtain the path. Furthermore, we are usually interested in search methods that minimize this combination averaged over all problems likely to be encountered. If the averaged ...
Contents
1 | |
17 | |
53 | |
CHAPTER 3 SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS | 99 |
CHAPTER 4 THE PREDICATE CALCULUS IN AI | 131 |
CHAPTER 5 RESOLUTION REFUTATION SYSTEMS | 161 |
CHAPTER 6 RULEBASED DEDUCTION SYSTEMS | 193 |
CHAPTER 7 BASIC PLANGENERATING SYSTEMS | 275 |
CHAPTER 8 ADVANCED PLANGENERATING SYSTEMS | 321 |
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS | 361 |
PROSPECTUS | 417 |
BIBLIOGRAPHY | 429 |
AUTHOR INDEX | 467 |
SUBJECT INDEX | 471 |